Publication details

Carlos Pérez-Penichet, Dilushi Piumwardane, Christian Rohner and Thiemo Voigt A Fast Carrier Scheduling Algorithm for Battery-free Sensor Tags in Commodity Wireless Networks. In IEEE INFOCOM 2020 - IEEE Conference on Computer Communications, IEEE INFOCOM ’20. (2020).

Abstract:

New battery-free sensor tags that interoperate with unmodified standard IoT devices and protocols can extend a sensor network’s capabilities in a scalable and cost-effective manner. The tags achieve battery-free operation through backscatter-related techniques, while the standard IoT devices can provide the necessary unmodulated carrier, avoiding additional dedicated infrastructure. However, this approach requires coordination between nodes transmitting, receiving and generating carrier, adds extra latency and energy consumption to already constrained devices, and increases interference and contention in the shared spectrum. We present a scheduling mechanism that optimizes the use of carrier generators, minimizing any disruptions to the regular nodes. We employ time slots to coordinate the unmodulated carrier while minimizing latency, energy consumption and overhead radio emissions. We propose an efficient scheduling algorithm that parallelizes communications with battery-free tags when possible and shares carriers among multiple tags concurrently. In our evaluation we demonstrate the feasibility and reliability of our approach in testbed experiments. We find that we can significantly reduce the excess latency and energy consumption caused by the addition of sensor tags when compared to sequential interrogation. We show the improvements tend to improve with the network size and that our solution is close to optimal in average.

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BibTeX:

 @inproceedings{perez-penichet_fast_2020,
  title = {A {Fast} {Carrier} {Scheduling} {Algorithm} for {Battery}-free {Sensor} {Tags} in {Commodity} {Wireless} {Networks}},
  series = { {IEEE} {INFOCOM} '20},
  abstract = {New battery-free sensor tags that interoperate with unmodified standard IoT devices and protocols can extend a sensor network's capabilities in a scalable and cost-effective manner. The tags achieve battery-free operation through backscatter-related techniques, while the standard IoT devices can provide the necessary unmodulated carrier, avoiding additional dedicated infrastructure. However, this approach requires coordination between nodes transmitting, receiving and generating carrier, adds extra latency and energy consumption to already constrained devices, and increases interference and contention in the shared spectrum. We present a scheduling mechanism that optimizes the use of carrier generators, minimizing any disruptions to the regular nodes. We employ time slots to coordinate the unmodulated carrier while minimizing latency, energy consumption and overhead radio emissions. We propose an efficient scheduling algorithm that parallelizes communications with battery-free tags when possible and shares carriers among multiple tags concurrently. In our evaluation we demonstrate the feasibility and reliability of our approach in testbed experiments. We find that we can significantly reduce the excess latency and energy consumption caused by the addition of sensor tags when compared to sequential interrogation. We show the improvements tend to improve with the network size and that our solution is close to optimal in average.},
  booktitle = { {IEEE} {INFOCOM} 2020 - {IEEE} {Conference} on {Computer} {Communications}},
  author = {Pérez-Penichet, Carlos and {Dilushi Piumwardane} and {Christian Rohner} and {Thiemo Voigt}},
  year = {2020},
  keywords = {Approximation algorithms, approximation theory, autonomous wireless devices, cloud computing, completion time, Computational modeling, computing equilibria, computing tasks, decentralized algorithm, edge cloud operator, Edge computing, edge computing resource management, game theory, Games, joint allocation, mobile computing, resource allocation, Resource management, selfish computation offloading, Stackelberg equilibria, Stackelberg game, static resource allocation, Task analysis, Wireless communication, wireless computing resource allocation}
}
 

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